Water allocation using game theory under climate change impact (case study: Zarinehrood)
The combined effects of climate change and growing water demand due to population growth, industrial and agricultural developments cause an increase in water scarcity and the subsequent environmental crisis in river basins, which results in conflicts over the property rights and allocation agreement...
Guardado en:
| Autores principales: | , |
|---|---|
| Formato: | article |
| Lenguaje: | EN |
| Publicado: |
IWA Publishing
2021
|
| Materias: | |
| Acceso en línea: | https://doaj.org/article/8a28f7115da74ab6ac10995257c186af |
| Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
| Sumario: | The combined effects of climate change and growing water demand due to population growth, industrial and agricultural developments cause an increase in water scarcity and the subsequent environmental crisis in river basins, which results in conflicts over the property rights and allocation agreements. Thus, an integrated, sustainable and efficient water allocation considering changes in water resources due to climate change and change of users' demands is necessary. In this study, the drainage basin of Zarinehrood was chosen to evaluate the function of selective methods. Assessing climate change impact scenarios of the Fifth IPCC reports, e.g., RCP2.6, RCP4.5, RCP6.0 and RCP8.5, have been used. For downscaling outputs of GCMs an artificial neural network (ANN) and for bias correction a quantile mapping (QM) method have been used. Using a bargaining game and the Nash bargaining solution (NBS) with two methods, one symmetric and two AHP methods, the water available for users was allocated. Results indicate an overall increase in temperature and precipitation in the basin. In bargaining game solutions, AHP provided better utilities for players than the symmetric method. These results show that with water management programs and use of a cooperative bargaining game, water allocation can be done in an efficient way. HIGHLIGHTS
Using ANN for downscaling.;
Using QM for bias correction.;
Using game theory for allocation.;
Using AHP method for calculating negotiation power.;
Evaluating all of the methods.; |
|---|